Location: Woodlawn,MD
Security Clearance: Must be able to obtain and maintain a public trust clearance
Job Type: Full-Time
Target Salary Range*: $130,000 - $180,000
*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary
Develop and maintain advanced data processing and entity resolution solutions using Python and SQL on enterprise data platforms. Support data cleansing, validation, optimization, testing, deployment, and monitoring while maintaining data integrity, security, reproducibility, and privacy standards.
Design, implement, and maintain advanced data processing and entity resolution pipelines using Python and SQL on enterprise data platforms.
Support end-to-end delivery from data validation and testing through deployment and post-implementation monitoring.
Clean, transform, and manage large-scale datasets from diverse and complex sources.
Ensure data integrity, reliability, and security.
Optimize complex SQL queries and database operations to support efficient data access, processing, and scalability.
Participate in code reviews and enforce version control.
Uphold best practices for code quality, reproducibility, data privacy, and security.
Bachelor’s degree in Statistics, Applied Mathematics, Computer Science, or Information Science with experience in NLP, Text Processing, Information Extraction, Python, SQL, Regex, and specialized libraries/frameworks. [Required]
Master’s degree with 10+ years of experience, Bachelor’s degree with 12+ years of experience, or 18+ years of experience in lieu of a degree. [Required]
10+ years of overall experience in the IT industry. [Required]
Strong practical experience with Natural Language Processing (NLP), Text Processing, and Information Extraction. [Required]
Practical knowledge of Named Entity Recognition and Address Standardization for extracting and cleaning unstructured text data. [Required]
Deep understanding of data matching strategies, including Blocking and Indexing, String Distance Metrics, and Phonetic Encoding. [Required]
Experience applying TF-IDF and Cosine Similarity for text comparisons and information retrieval. [Required]
Strong Python development skills for building analytics solutions and manipulating data. [Required]
Advanced SQL proficiency for complex data querying, optimization, and database operations. [Required]
Practical experience using Regex for advanced text processing, data cleansing, and pattern matching. [Required]
Familiarity with specialized libraries and frameworks, including:
Linkage libraries such as Splink/FastLink, Dedupe, or recordlinkage.
Core Python data science libraries, specifically spaCy for NLP tasks and Scikit-Learn for general machine learning and clustering.
Familiarity with code reviews, version control, and maintaining data security and reproducibility standards. [Required]
Excellent communication skills. [Required]
Ability to obtain and maintain a public trust clearance. [Required]
Willingness to work on-site at SSA HQ in Woodlawn, MD, 5 days a week. [Required]
Prior experience delivering IT or data initiatives within federal, state, or local government environments.
Experience retrieving, migrating, and manipulating data from legacy and distributed systems, including PostgreSQL, DB2, Oracle, SQL Server, and Hadoop, as well as unstructured flat files.
Experience utilizing Jenkins to automate continuous integration, testing, and deployment (CI/CD) for data validation pipelines.
Experience with pipeline automation tools to schedule and monitor complex data cleansing jobs.
Ability to operate independently, take ownership of data pipeline architectures, and drive projects from data discovery through post-implementation.
Strong ability to translate complex algorithmic decisions, such as probabilistic match thresholds, into clear business logic for executive leadership and non-technical stakeholders.
Excellent problem-solving skills and proven verbal and written communication skills when collaborating across cross-functional teams.
Job details are sourced from the employer's original posting.
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